PT Unknown
AU David Aldavert
   Marçal Rusiñol
   Ricardo Toledo
   Josep Llados
TI Integrating Visual and Textual Cues for Query-by-String Word Spotting
BT 12th International Conference on Document Analysis and Recognition
PY 2013
BP 511
EP 515
DI 10.1109/ICDAR.2013.108
AB In this paper, we present a word spotting framework that follows the query-by-string paradigm where word images are represented both by textual and visual representations. The textual representation is formulated in terms of character $n$-grams while the visual one is based on the bag-of-visual-words scheme. These two representations are merged together and projected to a sub-vector space. This transform allows to, given a textual query, retrieve word instances that were only represented by the visual modality. Moreover, this statistical representation can be used together with state-of-the-art indexation structures in order to deal with large-scale scenarios. The proposed method is evaluated using a collection of historical documents outperforming state-of-the-art performances.
ER